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y <- aspol |>
  distinct(kunta) |>
  left_join(taantuvat) |>
  filter(!is.na(luokka)) |>
  mutate(luokka = forcats::fct_collapse(luokka,
                                        Kasvava = c("Voimakkaasti kasvava",
                                                    "Kasvava",
                                                    "Hieman kasvava"), 
                                        Taantuva = c("Hieman taantuva",
                                                     "Taantuva",
                                                     "Voimakkaasti taantuva")))
y
#> # A tibble: 66 × 5
#>    kunta       vaesto kokmuutos_2010_2022 suht_muutos_2010_2022 luokka  
#>    <chr>        <int>               <int>                 <dbl> <fct>   
#>  1 Enontekiö     1876                 -71                 -3.78 Taantuva
#>  2 Espoo       247970               60944                 24.6  Kasvava 
#>  3 Eura         12507               -1278                -10.2  Taantuva
#>  4 Hartola       3355                -814                -24.3  Taantuva
#>  5 Hattula       9657                -266                 -2.75 Taantuva
#>  6 Helsinki    588549               80678                 13.7  Kasvava 
#>  7 Huittinen    10663                -955                 -8.96 Taantuva
#>  8 Hyvinkää     45489                1527                  3.36 Kasvava 
#>  9 Hämeenlinna  66829                1588                  2.38 Kasvava 
#> 10 Iitti         7005                -557                 -7.95 Taantuva
#> 11 Imatra       28540               -3468                -12.2  Taantuva
#> 12 Inkoo         5546                -225                 -4.06 Taantuva
#> 13 Joensuu      73305                4809                  6.56 Kasvava 
#> 14 Juva          6962               -1295                -18.6  Taantuva
#> 15 Järvenpää    38680                6922                 17.9  Kasvava 
#> 16 Kaarina      30911                5088                 16.5  Kasvava 
#> 17 Kalajoki     12562                -205                 -1.63 Taantuva
#> 18 Kauniainen    8689                1667                 19.2  Kasvava 
#> 19 Kemiönsaari   7191                -749                -10.4  Taantuva
#> 20 Kerava       34282                3843                 11.2  Kasvava 
#> # ℹ 46 more rows
X <- aspol |> 
  preprocess_corpus() |> 
  corpus_to_dtm(kunta, LEMMA) |>
  dfm_subset(docname_ %in% y$kunta)
X
#> Document-feature matrix of: 66 documents, 3,061 features (76.84% sparse) and 0 docvars.
#>              features
#> docs          A#talo III Vapaa#aika aiheuttaa aika aika#väli ajatella ala alhainen alku alku#peräinen alku#puoli antaa arava#laina arava#rajoitus arvioida asettaa asia asiakas asian#mukainen
#>   Enontekiö        3   1          1         3    7         1        1   1        1    1             1          1     3           1              1        1       2    3       3              1
#>   Espoo            0   0          0         1   18         3        0   3        4    1             1          0     2           0              0        9      10    3       1              0
#>   Eura             0   0          0         1    5         0        0   0        1    0             0          0     1           0              0        3       1    1       6              0
#>   Hartola          0   0          1         2    5         0        0   1        0    0             0          0     0           0              0        3       0    0       0              0
#>   Hattula          0   0          0         0    6         0        0   0        0    1             0          0     1           0              0        0       1    1       0              0
#>   Helsinki         0   0          0         3   46         4        0   5        5   12             0          1     7           0              0       26      13    8       6              1
#>   Huittinen        2   0          0         0   13         1        5   2        2    0             0          0     3           0              0        4       3   13       4              0
#>   Hyvinkää         0   0          0         0    1         0        0   0        0    0             0          0     0           0              0        1       0    0       0              0
#>   Hämeenlinna      0   0          3         3    1         0        0   2        0    1             0          0     3           0              0        2       0   29       3              0
#>   Iitti            0   0          0         0    0         0        0   0        0    1             0          0     5           0              0        0       1    0       0              0
#>   Imatra           0   0          0         0    2         0        0   1        0    0             0          0     0           0              0        2       0    1       0              0
#>   Inkoo            0   0          0         1   11         1        0   0        1    2             0          0     4           0              0        0       5    2       0              0
#>   Joensuu          0   0          0         1   33         2        1   0        4    4             1          0     2           0              1        9      13    5       4              0
#>   Juva             0   0          0         2   13         5        0   1        2    3             0          0     2           1              0        1       2    2       3              0
#>   Järvenpää        0   0          0         0    2         0        0   0        0    0             0          0     1           0              0        0       3    2       0              0
#>   Kaarina          0   0          1         2   15         6        0   0        0    1             0          0     4           0              0        4       4    3       0              0
#>   Kalajoki         0   0          0         0    1         0        0   0        0    0             0          0     0           0              0        2       0    0       0              0
#>   Kauniainen       0   0          0         2   14         0        1   0        0    1             0          1     4           0              0       12       6    1       3              0
#>   Kemiönsaari      0   0          3         3   12         1        1   1        1    3             2          0    14           0              0        3       3    1       2              0
#>   Kerava           0   0          0         2    0         0        0   0        0    0             0          0     3           0              0        2       5    0       0              0
#> [ reached max_ndoc ... 46 more documents, reached max_nfeat ... 3,041 more features ]
optimal_k <- c(5, 15, 18, 21)
system.time(
  theta_matrix <- foreach(k = optimal_k) %dofuture% {
    # get_doc_topic_prob(X, k = k)
    lda <- topicmodels::LDA(quanteda::convert(X, to = "tm"), k = k, control = list(seed = 1234))
    lda |>
      tidytext::tidy(matrix = "gamma") |>
      tidytext::cast_dfm(document, topic, gamma)
  }
)
#>    user  system elapsed 
#>   2.758   0.097  75.747

names(theta_matrix) <- paste0("k_", optimal_k)
theta_matrix
#> $k_5
#> Document-feature matrix of: 66 documents, 5 features (0.00% sparse) and 0 docvars.
#>              features
#> docs                     1            2            3            4            5
#>   Enontekiö   8.606223e-05 8.606244e-05 9.996557e-01 8.606532e-05 8.606483e-05
#>   Espoo       6.123387e-01 3.875888e-01 2.416384e-05 2.416435e-05 2.416383e-05
#>   Eura        8.310256e-05 8.311158e-05 8.603327e-01 8.310812e-05 1.394180e-01
#>   Hartola     1.015523e-04 4.119933e-02 9.584960e-01 1.015670e-04 1.015596e-04
#>   Hattula     2.224271e-01 1.345043e-04 1.292242e-01 3.728322e-01 2.753820e-01
#>   Helsinki    1.227323e-05 9.999509e-01 1.227255e-05 1.227257e-05 1.227253e-05
#>   Huittinen   4.123488e-02 3.371053e-02 2.181909e-01 3.607065e-01 3.461573e-01
#>   Hyvinkää    4.351080e-02 4.342484e-01 1.878331e-04 1.496725e-01 3.723805e-01
#>   Hämeenlinna 4.344616e-05 1.818009e-02 4.069894e-01 2.753202e-01 2.994669e-01
#>   Iitti       6.114263e-01 2.092173e-04 3.621206e-01 2.603466e-02 2.092140e-04
#>   Imatra      2.408684e-04 3.992987e-01 2.408956e-04 3.754274e-01 2.247921e-01
#>   Inkoo       6.525282e-01 4.518005e-02 5.826246e-05 1.392811e-01 1.629523e-01
#>   Joensuu     7.365549e-02 1.868584e-01 2.737192e-02 4.128733e-01 2.992409e-01
#>   Juva        5.972653e-05 5.973280e-05 9.997611e-01 5.973343e-05 5.973663e-05
#>   Järvenpää   1.106307e-04 6.594140e-01 1.106293e-04 2.600977e-01 8.026703e-02
#>   Kaarina     7.894466e-01 1.040432e-01 3.239381e-05 3.239659e-05 1.064454e-01
#>   Kalajoki    6.766848e-04 4.731515e-01 1.204212e-01 2.859377e-01 1.198129e-01
#>   Kauniainen  2.912906e-01 5.337143e-01 4.672361e-02 2.534518e-02 1.029263e-01
#>   Kemiönsaari 9.428661e-01 2.758007e-05 5.705113e-02 2.758330e-05 2.758213e-05
#>   Kerava      9.997232e-01 6.919711e-05 6.918496e-05 6.919125e-05 6.919199e-05
#> [ reached max_ndoc ... 46 more documents ]
#> 
#> $k_15
#> Document-feature matrix of: 66 documents, 15 features (0.00% sparse) and 0 docvars.
#>              features
#> docs                     1            2            3            4            5            6            7            8            9           10           11           12           13           14           15
#>   Enontekiö   1.679843e-05 1.679843e-05 9.997648e-01 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05 1.679843e-05
#>   Espoo       3.943024e-03 4.715534e-06 4.715534e-06 4.715534e-06 4.715534e-06 4.715534e-06 7.406924e-01 4.715534e-06 2.553080e-01 4.715534e-06 4.715534e-06 4.715534e-06 4.715534e-06 4.715534e-06 4.715534e-06
#>   Eura        1.622202e-05 1.622202e-05 9.378262e-01 1.622202e-05 1.622202e-05 1.622202e-05 1.622202e-05 6.196288e-02 1.622202e-05 1.622202e-05 1.622202e-05 1.622202e-05 1.622202e-05 1.622202e-05 1.622202e-05
#>   Hartola     1.982413e-05 1.982413e-05 9.997225e-01 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05 1.982413e-05
#>   Hattula     1.372363e-01 2.625442e-05 2.625442e-05 2.625442e-05 2.625442e-05 2.625442e-05 2.625442e-05 2.625442e-05 2.625442e-05 2.625442e-05 3.133042e-01 2.199454e-01 1.580278e-01 2.625442e-05 1.712238e-01
#>   Helsinki    2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 9.999665e-01 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06 2.395043e-06
#>   Huittinen   8.052335e-06 8.052335e-06 8.740043e-02 8.052335e-06 8.052335e-06 8.052335e-06 8.052335e-06 8.052335e-06 8.052335e-06 8.052335e-06 1.742530e-01 8.052335e-06 8.052335e-06 8.052335e-06 7.382499e-01
#>   Hyvinkää    1.728037e-01 1.143897e-01 3.666711e-05 3.666711e-05 3.666711e-05 3.666711e-05 3.666711e-05 3.308893e-01 3.666711e-05 3.815139e-01 3.666711e-05 3.666711e-05 3.666711e-05 3.666711e-05 3.666711e-05
#>   Hämeenlinna 8.479025e-06 3.341023e-02 1.712503e-02 8.479025e-06 1.687146e-02 8.479025e-06 8.479025e-06 8.479025e-06 8.479025e-06 7.798250e-01 8.479025e-06 1.085918e-01 8.479025e-06 4.410009e-02 8.479025e-06
#>   Iitti       4.084273e-05 4.084273e-05 4.084273e-05 2.902966e-02 7.970549e-02 8.268938e-01 4.084273e-05 4.084273e-05 6.392182e-02 4.084273e-05 4.084273e-05 4.084273e-05 4.084273e-05 4.084273e-05 4.084273e-05
#>   Imatra      4.702945e-05 4.702945e-05 4.702945e-05 4.702945e-05 4.702945e-05 4.702945e-05 4.702945e-05 4.702945e-05 4.702945e-05 9.623616e-01 4.702945e-05 4.702945e-05 4.702945e-05 3.702700e-02 4.702945e-05
#>   Inkoo       6.226447e-01 1.137132e-05 1.137132e-05 1.137132e-05 1.137132e-05 1.027854e-01 1.137132e-05 1.137132e-05 1.137132e-05 2.018057e-01 1.137132e-05 1.137132e-05 7.263912e-02 1.137132e-05 1.137132e-05
#>   Joensuu     3.770942e-06 3.770942e-06 3.770942e-06 3.770942e-06 3.770942e-06 3.770942e-06 7.360047e-02 3.770942e-06 3.770942e-06 5.386418e-01 3.770942e-06 3.770942e-06 3.770942e-06 1.460087e-01 2.417076e-01
#>   Juva        1.165810e-05 1.165810e-05 9.998368e-01 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05 1.165810e-05
#>   Järvenpää   2.159393e-05 2.159393e-05 2.159393e-05 2.159393e-05 2.159393e-05 2.159393e-05 2.159393e-05 1.820316e-01 9.147967e-02 2.159393e-05 2.159393e-05 6.420998e-02 2.159393e-05 6.620412e-01 2.159393e-05
#>   Kaarina     7.925062e-01 6.322104e-06 6.322104e-06 6.322104e-06 2.074116e-01 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06 6.322104e-06
#>   Kalajoki    1.436383e-01 1.322321e-04 1.104014e-01 1.322321e-04 1.322321e-04 1.322321e-04 1.322321e-04 1.322321e-04 1.588870e-01 1.322321e-04 1.322321e-04 1.322321e-04 1.322321e-04 1.322321e-04 5.856187e-01
#>   Kauniainen  6.819530e-06 6.819530e-06 6.819530e-06 6.819530e-06 6.819530e-06 6.819530e-06 6.819530e-06 6.819530e-06 1.483970e-02 6.819530e-06 6.819530e-06 6.819530e-06 9.850716e-01 6.819530e-06 6.819530e-06
#>   Kemiönsaari 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 9.999246e-01 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06 5.383026e-06
#>   Kerava      9.998109e-01 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05 1.350486e-05
#> [ reached max_ndoc ... 46 more documents ]
#> 
#> $k_18
#> Document-feature matrix of: 66 documents, 18 features (0.00% sparse) and 0 docvars.
#>              features
#> docs                     1            2            3            4            5            6            7            8            9           10           11           12           13           14           15           16           17           18
#>   Enontekiö   1.299809e-05 1.299809e-05 9.997790e-01 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05 1.299809e-05
#>   Espoo       1.048575e-02 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 2.222091e-01 3.648683e-06 7.672504e-01 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06 3.648683e-06
#>   Eura        1.255207e-05 1.255207e-05 8.854954e-01 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.255207e-05 1.143038e-01 1.255207e-05
#>   Hartola     1.533932e-05 1.533932e-05 9.940542e-01 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 1.533932e-05 5.700389e-03 1.533932e-05 1.533932e-05
#>   Hattula     1.391091e-01 2.031504e-05 2.031504e-05 1.349516e-01 2.031504e-05 2.031504e-05 2.031504e-05 6.140553e-02 2.031504e-05 2.031504e-05 2.958494e-01 2.097024e-01 1.587382e-01 2.031504e-05 2.031504e-05 2.031504e-05 2.031504e-05 2.031504e-05
#>   Helsinki    1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 1.853179e-06 9.999685e-01 1.853179e-06 1.853179e-06
#>   Huittinen   6.230581e-06 6.230581e-06 1.811657e-02 9.835076e-02 6.230581e-06 6.230581e-06 6.230581e-06 6.230581e-06 6.230581e-06 6.230581e-06 1.839712e-01 6.230581e-06 6.230581e-06 6.230581e-06 6.994742e-01 6.230581e-06 6.230581e-06 6.230581e-06
#>   Hyvinkää    1.472571e-01 1.553885e-01 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05 3.135304e-01 2.837244e-05 3.834268e-01 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05 2.837244e-05
#>   Hämeenlinna 6.560740e-06 1.754107e-02 5.719255e-02 4.756925e-02 6.560740e-06 6.560740e-06 6.560740e-06 6.560740e-06 6.560740e-06 6.165323e-01 6.560740e-06 1.871120e-01 6.560740e-06 3.511489e-02 6.560740e-06 6.560740e-06 3.886575e-02 6.560740e-06
#>   Iitti       3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 8.139641e-01 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 3.160361e-05 9.147191e-02 5.964667e-02 3.447485e-02
#>   Imatra      3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05 2.599695e-01 3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05 7.394482e-01 3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05 3.639107e-05
#>   Inkoo       5.074923e-01 8.798713e-06 8.798713e-06 8.798713e-06 8.798713e-06 1.722328e-01 8.798713e-06 5.763348e-02 8.798713e-06 2.245221e-01 8.798713e-06 8.798713e-06 3.800494e-02 8.798713e-06 8.798713e-06 8.798713e-06 8.798713e-06 8.798713e-06
#>   Joensuu     2.917794e-06 2.917794e-06 2.917794e-06 2.917794e-06 2.917794e-06 2.917794e-06 2.039345e-02 2.917794e-06 2.917794e-06 8.057260e-01 2.917794e-06 2.917794e-06 2.917794e-06 3.066730e-03 1.707730e-01 2.917794e-06 2.917794e-06 2.917794e-06
#>   Juva        9.020618e-06 9.020618e-06 9.998466e-01 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06 9.020618e-06
#>   Järvenpää   1.670878e-05 1.670878e-05 1.670878e-05 1.670878e-05 1.670878e-05 1.670878e-05 1.670878e-05 2.000145e-01 1.670878e-05 1.670878e-05 1.670878e-05 1.670878e-05 1.670878e-05 7.607614e-01 1.670878e-05 3.897347e-02 1.670878e-05 1.670878e-05
#>   Kaarina     1.062195e-01 4.891787e-06 4.891787e-06 4.891787e-06 8.937023e-01 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06 4.891787e-06
#>   Kalajoki    2.050284e-01 1.023296e-04 1.433066e-01 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.023296e-04 1.753466e-01 4.748858e-01 1.023296e-04 1.023296e-04 1.023296e-04
#>   Kauniainen  5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 9.999103e-01 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06 5.276678e-06
#>   Kemiönsaari 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 9.999292e-01 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06 4.165163e-06
#>   Kerava      9.998224e-01 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05 1.044959e-05
#> [ reached max_ndoc ... 46 more documents ]
#> 
#> $k_21
#> Document-feature matrix of: 66 documents, 21 features (0.00% sparse) and 0 docvars.
#>              features
#> docs                     1            2            3            4            5            6            7            8            9           10           11           12           13           14           15           16           17           18           19           20
#>   Enontekiö   1.182627e-05 1.182627e-05 9.997635e-01 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05 1.182627e-05
#>   Espoo       2.428234e-02 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 8.899351e-02 3.319777e-06 8.866644e-01 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06 3.319777e-06
#>   Eura        1.142047e-05 1.142047e-05 9.735563e-01 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 1.142047e-05 2.622674e-02 1.142047e-05 1.142047e-05 1.142047e-05
#>   Hartola     1.395640e-05 1.395640e-05 7.349023e-01 1.395640e-05 1.395640e-05 2.648326e-01 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05 1.395640e-05
#>   Hattula     1.416460e-01 1.848342e-05 1.848342e-05 1.173190e-01 1.848342e-05 2.098230e-02 1.848342e-05 3.931001e-02 1.848342e-05 1.848342e-05 2.618716e-01 2.316703e-01 9.415671e-02 1.848342e-05 1.848342e-05 1.848342e-05 1.848342e-05 1.848342e-05 1.848342e-05 1.848342e-05
#>   Helsinki    1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06 9.999663e-01 1.686130e-06 1.686130e-06 1.686130e-06 1.686130e-06
#>   Huittinen   5.668917e-06 2.521769e-01 5.668917e-06 2.347533e-01 5.668917e-06 8.459530e-02 5.668917e-06 5.668917e-06 5.668917e-06 5.668917e-06 2.268407e-01 5.668917e-06 5.668917e-06 5.668917e-06 1.719354e-01 5.668917e-06 5.668917e-06 5.668917e-06 2.961340e-02 5.668917e-06
#>   Hyvinkää    2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 4.146677e-01 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 2.581414e-05 5.848419e-01 2.581414e-05
#>   Hämeenlinna 5.969311e-06 5.969311e-06 6.728307e-01 5.969311e-06 5.969311e-06 5.969311e-06 5.969311e-06 5.969311e-06 5.969311e-06 1.123070e-01 5.969311e-06 1.757731e-01 5.969311e-06 5.969311e-06 5.969311e-06 5.969311e-06 5.969311e-06 3.898767e-02 5.969311e-06 5.969311e-06
#>   Iitti       2.875386e-05 2.875386e-05 2.875386e-05 2.875386e-05 2.875386e-05 2.956050e-01 2.875386e-05 2.875386e-05 1.439365e-01 2.875386e-05 2.875386e-05 2.875386e-05 2.875386e-05 2.875386e-05 2.875386e-05 2.875386e-05 5.930096e-02 6.485691e-02 2.875386e-05 2.875386e-05
#>   Imatra      3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 9.993378e-01 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05 3.310944e-05
#>   Inkoo       8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.233246e-02 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 2.494317e-01 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06 8.005519e-06
#>   Joensuu     2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 1.982008e-03 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 9.979676e-01 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06 2.654775e-06
#>   Juva        8.207417e-06 8.207417e-06 9.998359e-01 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06 8.207417e-06
#>   Järvenpää   1.520237e-05 1.520237e-05 1.520237e-05 1.520237e-05 1.520237e-05 1.520237e-05 1.520237e-05 2.101349e-01 1.520237e-05 1.520237e-05 1.520237e-05 1.247352e-01 1.520237e-05 3.142443e-01 1.520237e-05 1.718328e-02 1.520237e-05 1.520237e-05 1.926832e-01 1.407911e-01
#>   Kaarina     4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 9.999110e-01 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06 4.450817e-06
#>   Kalajoki    3.150246e-01 5.986347e-01 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 8.466496e-02 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05 9.309507e-05
#>   Kauniainen  4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 9.999040e-01 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06 4.801010e-06
#>   Kemiönsaari 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06 3.789697e-06
#>   Kerava      9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.507553e-06 9.998098e-01 9.507553e-06
#> [ reached max_ndoc ... 46 more documents, reached max_nfeat ... 1 more feature ]
xgb_data <- lapply(theta_matrix, get_train_test_data, y, split_train_test(y, luokka, kunta))
xgb_data
#> $k_5
#> $k_5$Train
#> xgb.DMatrix  dim: 47 x 5  info: label  colnames: yes
#> 
#> $k_5$Test
#> xgb.DMatrix  dim: 19 x 5  info: label  colnames: yes
#> 
#> 
#> $k_15
#> $k_15$Train
#> xgb.DMatrix  dim: 47 x 15  info: label  colnames: yes
#> 
#> $k_15$Test
#> xgb.DMatrix  dim: 19 x 15  info: label  colnames: yes
#> 
#> 
#> $k_18
#> $k_18$Train
#> xgb.DMatrix  dim: 47 x 18  info: label  colnames: yes
#> 
#> $k_18$Test
#> xgb.DMatrix  dim: 19 x 18  info: label  colnames: yes
#> 
#> 
#> $k_21
#> $k_21$Train
#> xgb.DMatrix  dim: 47 x 21  info: label  colnames: yes
#> 
#> $k_21$Test
#> xgb.DMatrix  dim: 19 x 21  info: label  colnames: yes
gs <- tidyr::expand_grid(
  booster = "gbtree",
  eta = seq(0.01, 0.1, by = 0.2),
  max_depth = seq(3, 7, by = 1),
  gamma = seq(0, 4, by = 2),
  subsample = seq(0.5, 1, by = 0.25),
  colsample_bylevel = seq(0.5, 1, by = 0.25),
  nrounds = seq(5, 55, by = 25),
  objective = "binary:logistic",
  num_parallel_tree = 2
)
gs
#> # A tibble: 405 × 9
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl>
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2
#> # ℹ 385 more rows
system.time(
  gs_list <- lapply(xgb_data, function(x) {
    gs |> mutate(xgb_model = purrr::pmap(gs, function(...) mod(x[["Train"]], ...), .progress = TRUE))
  })
)
#>  ■■■■■■■■■■■■■■                    44% |  ETA:  2s
#>  ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■    97% |  ETA:  0s
#>  ■■■■■■■■■■■■■■■■■■■■■             68% |  ETA:  1s
#>  ■■■■■■■■■■■■                      38% |  ETA:  3s
#>    user  system elapsed 
#>  51.039   3.581  16.368

gs_list
#> $k_5
#> # A tibble: 405 × 10
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model 
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>    
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr>
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr>
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr>
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr>
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr>
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr>
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr>
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr>
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr>
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr>
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr>
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr>
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr>
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr>
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr>
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr>
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr>
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr>
#> # ℹ 385 more rows
#> 
#> $k_15
#> # A tibble: 405 × 10
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model 
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>    
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr>
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr>
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr>
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr>
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr>
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr>
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr>
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr>
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr>
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr>
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr>
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr>
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr>
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr>
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr>
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr>
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr>
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr>
#> # ℹ 385 more rows
#> 
#> $k_18
#> # A tibble: 405 × 10
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model 
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>    
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr>
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr>
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr>
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr>
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr>
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr>
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr>
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr>
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr>
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr>
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr>
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr>
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr>
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr>
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr>
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr>
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr>
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr>
#> # ℹ 385 more rows
#> 
#> $k_21
#> # A tibble: 405 × 10
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model 
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>    
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr>
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr>
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr>
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr>
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr>
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr>
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr>
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr>
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr>
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr>
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr>
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr>
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr>
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr>
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr>
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr>
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr>
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr>
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr>
#> # ℹ 385 more rows
gs_list <- map2(xgb_data, gs_list, function(xgb_dat, xgb_mod) {
  xgb_mod |> mutate(error = purrr::map_dbl(xgb_model, function(mod) {
    compute_error(mod, xgb_dat[["Test"]])
  }))
}  )
gs_list
#> $k_5
#> # A tibble: 405 × 11
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model   error
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>      <dbl>
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr> 0.474 
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr> 0.211 
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr> 0.158 
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr> 0.158 
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr> 0.105 
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr> 0.105 
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr> 0.105 
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr> 0.105 
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr> 0.105 
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr> 0.105 
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr> 0.105 
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr> 0.158 
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr> 0.105 
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr> 0.158 
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr> 0.158 
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr> 0.0526
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr> 0.158 
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr> 0.158 
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr> 0.105 
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr> 0.158 
#> # ℹ 385 more rows
#> 
#> $k_15
#> # A tibble: 405 × 11
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model  error
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>     <dbl>
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr> 0.263
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr> 0.158
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr> 0.263
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr> 0.211
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr> 0.211
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr> 0.158
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr> 0.211
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr> 0.263
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr> 0.211
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr> 0.316
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr> 0.211
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr> 0.211
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr> 0.263
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr> 0.263
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr> 0.263
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr> 0.263
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr> 0.263
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr> 0.263
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr> 0.316
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr> 0.263
#> # ℹ 385 more rows
#> 
#> $k_18
#> # A tibble: 405 × 11
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model  error
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>     <dbl>
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr> 0.316
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr> 0.316
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr> 0.263
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr> 0.316
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr> 0.316
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr> 0.263
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr> 0.158
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr> 0.211
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr> 0.211
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr> 0.421
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr> 0.263
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr> 0.368
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr> 0.158
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr> 0.316
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr> 0.316
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr> 0.368
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr> 0.263
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr> 0.316
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr> 0.421
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr> 0.211
#> # ℹ 385 more rows
#> 
#> $k_21
#> # A tibble: 405 × 11
#>    booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model  error
#>    <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>     <dbl>
#>  1 gbtree   0.01         3     0      0.5               0.5        5 binary:logistic                 2 <xgb.Bstr> 0.579
#>  2 gbtree   0.01         3     0      0.5               0.5       30 binary:logistic                 2 <xgb.Bstr> 0.368
#>  3 gbtree   0.01         3     0      0.5               0.5       55 binary:logistic                 2 <xgb.Bstr> 0.368
#>  4 gbtree   0.01         3     0      0.5               0.75       5 binary:logistic                 2 <xgb.Bstr> 0.263
#>  5 gbtree   0.01         3     0      0.5               0.75      30 binary:logistic                 2 <xgb.Bstr> 0.368
#>  6 gbtree   0.01         3     0      0.5               0.75      55 binary:logistic                 2 <xgb.Bstr> 0.421
#>  7 gbtree   0.01         3     0      0.5               1          5 binary:logistic                 2 <xgb.Bstr> 0.368
#>  8 gbtree   0.01         3     0      0.5               1         30 binary:logistic                 2 <xgb.Bstr> 0.368
#>  9 gbtree   0.01         3     0      0.5               1         55 binary:logistic                 2 <xgb.Bstr> 0.421
#> 10 gbtree   0.01         3     0      0.75              0.5        5 binary:logistic                 2 <xgb.Bstr> 0.474
#> 11 gbtree   0.01         3     0      0.75              0.5       30 binary:logistic                 2 <xgb.Bstr> 0.421
#> 12 gbtree   0.01         3     0      0.75              0.5       55 binary:logistic                 2 <xgb.Bstr> 0.368
#> 13 gbtree   0.01         3     0      0.75              0.75       5 binary:logistic                 2 <xgb.Bstr> 0.368
#> 14 gbtree   0.01         3     0      0.75              0.75      30 binary:logistic                 2 <xgb.Bstr> 0.368
#> 15 gbtree   0.01         3     0      0.75              0.75      55 binary:logistic                 2 <xgb.Bstr> 0.368
#> 16 gbtree   0.01         3     0      0.75              1          5 binary:logistic                 2 <xgb.Bstr> 0.421
#> 17 gbtree   0.01         3     0      0.75              1         30 binary:logistic                 2 <xgb.Bstr> 0.474
#> 18 gbtree   0.01         3     0      0.75              1         55 binary:logistic                 2 <xgb.Bstr> 0.368
#> 19 gbtree   0.01         3     0      1                 0.5        5 binary:logistic                 2 <xgb.Bstr> 0.474
#> 20 gbtree   0.01         3     0      1                 0.5       30 binary:logistic                 2 <xgb.Bstr> 0.474
#> # ℹ 385 more rows
results <- bind_rows(gs_list, .id = "lda_model")
results |>
  ggplot() +
  geom_boxplot(aes(error)) +
  labs(y="") +
  theme(axis.text.y = element_blank(), axis.ticks.y = element_blank()) +
  facet_wrap(~lda_model, nrow = 4)

results |> slice_max(order_by = -error, n = 1, by = lda_model, with_ties = FALSE)
#> # A tibble: 4 × 12
#>   lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds objective       num_parallel_tree xgb_model   error
#>   <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl> <chr>                       <dbl> <list>      <dbl>
#> 1 k_5       gbtree   0.01         3     0      0.75                 1       5 binary:logistic                 2 <xgb.Bstr> 0.0526
#> 2 k_15      gbtree   0.01         3     2      0.5                  1       5 binary:logistic                 2 <xgb.Bstr> 0.105 
#> 3 k_18      gbtree   0.01         3     0      0.5                  1       5 binary:logistic                 2 <xgb.Bstr> 0.158 
#> 4 k_21      gbtree   0.01         3     2      0.5                  1       5 binary:logistic                 2 <xgb.Bstr> 0.211
results |>
  mutate(importance = map2(results$lda_model, results$xgb_model, function(k_model, mdl) {
    results |> mutate(importance = tidyr::nest(
      xgb.importance(feature_names = colnames(xgb_data[[k_model]]),
                     model = mdl)
    ))
  }, .progress = TRUE))
#>  ■■■■■■■■                          24% |  ETA: 12s
#>  ■■■■■■■■■■■■■■                    44% |  ETA:  8s
#>  ■■■■■■■■■■■■■■■■■■■■              62% |  ETA:  6s
#>  ■■■■■■■■■■■■■■■■■■■■■■■■■■        83% |  ETA:  3s
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <list>
importance <-  map2(results$lda_model, results$xgb_model, function(k_model, mdl) {
  results |> mutate(importance = tidyr::nest(xgb.importance(feature_names = colnames(xgb_data[[k_model]]),
                 model = mdl)))
}, .progress = TRUE)
#>  ■■■■■■■■■                         25% |  ETA: 11s
#>  ■■■■■■■■■■■■■■                    44% |  ETA:  8s
#>  ■■■■■■■■■■■■■■■■■■■■              65% |  ETA:  5s
#>  ■■■■■■■■■■■■■■■■■■■■■■■■■■■       85% |  ETA:  2s
importance
#> [[1]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[2]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[3]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[4]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[5]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[6]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[7]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[8]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[9]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[10]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[11]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[12]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[13]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[14]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[15]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[16]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[17]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[18]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[19]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[20]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[21]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[22]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[23]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[24]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[25]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[26]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[27]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[28]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[29]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[30]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[31]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[32]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[33]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[34]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[35]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[36]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[37]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[38]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[39]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[40]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[41]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[42]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[43]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[44]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[45]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[46]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[47]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[48]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[49]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[50]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[51]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[52]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[53]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[54]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[55]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[56]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[57]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[58]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[59]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[60]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[61]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[62]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[63]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[64]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[65]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[66]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[67]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[68]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[69]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[70]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[71]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[72]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[73]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[74]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[75]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[76]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[77]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[78]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[79]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[80]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[81]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[82]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[83]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[84]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[85]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[86]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[87]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[88]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[89]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[90]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[91]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[92]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[93]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[94]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[95]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[96]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[97]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[98]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[99]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[100]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[101]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[102]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[103]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[104]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[105]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[106]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[107]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[108]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[109]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[110]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[111]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[112]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[113]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[114]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[115]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[116]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[117]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[118]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[119]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[120]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[121]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[122]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[123]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[124]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[125]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[126]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[127]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[128]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[129]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[130]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[131]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[132]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[133]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[134]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[135]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[136]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[137]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[138]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[139]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[140]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[141]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[142]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[143]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[144]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[145]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[146]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[147]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[148]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[149]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[150]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[151]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[152]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[153]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[154]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[155]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[156]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[157]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[158]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[159]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[160]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[161]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[162]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[163]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[164]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[165]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[166]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[167]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[168]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[169]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[170]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[171]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[172]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[173]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[174]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[175]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[176]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[177]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[178]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[179]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[180]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[181]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[182]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[183]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[184]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[185]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[186]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[187]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[188]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[189]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[190]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[191]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[192]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[193]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[194]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[195]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[196]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[197]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[198]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[199]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[200]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[201]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[202]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[203]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[204]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[205]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[206]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[207]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[208]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[209]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[210]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[211]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[212]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[213]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[214]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[215]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[216]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[217]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[218]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[219]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[220]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[221]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[222]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[223]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[224]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[225]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[226]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[227]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[228]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[229]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[230]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[231]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[232]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[233]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[234]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[235]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[236]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[237]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[238]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[239]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[240]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[241]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[242]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[243]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[244]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[245]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[246]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[247]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[248]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[249]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[250]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[251]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[252]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[253]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[254]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[255]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[256]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[257]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[258]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[259]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[260]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[261]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[262]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[263]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[264]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[265]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[266]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[267]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[268]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[269]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[270]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[271]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[272]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[273]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[274]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[275]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[276]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[277]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[278]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[279]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[280]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[281]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[282]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[283]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[284]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[285]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[286]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[287]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[288]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[289]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[290]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[291]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[292]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[293]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[294]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[295]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[296]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[297]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[298]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[299]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[300]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[301]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[302]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[303]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[304]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[305]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[306]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[307]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[308]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[309]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[310]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[311]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[312]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[313]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[314]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[315]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[316]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[317]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[318]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[319]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[320]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[321]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[322]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[323]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[324]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[325]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[326]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[327]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[328]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[329]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[330]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[331]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[332]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[333]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[334]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[335]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[336]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[337]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[338]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[339]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[340]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[341]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[342]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[343]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[344]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[345]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[346]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[347]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[348]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[349]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[350]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[351]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[352]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[353]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[354]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[355]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[356]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[357]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[358]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[359]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[360]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[361]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[362]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[363]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[364]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[365]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[366]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[367]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[368]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[369]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[370]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[371]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[372]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[373]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[374]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[375]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[376]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[377]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[378]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[379]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[380]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[381]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[382]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[383]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[384]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[385]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[386]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[387]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[388]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[389]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[390]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[391]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[392]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[393]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[394]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[395]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[396]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[397]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[398]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[399]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[400]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[401]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[402]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[403]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[404]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[405]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[406]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[407]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[408]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[409]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[410]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[411]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[412]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[413]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[414]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[415]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[416]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[417]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[418]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[419]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[420]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[421]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[422]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[423]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[424]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[425]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[426]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[427]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[428]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[429]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[430]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[431]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[432]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[433]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[434]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[435]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[436]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[437]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[438]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[439]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[440]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[441]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[442]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[443]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[444]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[445]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[446]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[447]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[448]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[449]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[450]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[451]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[452]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[453]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[454]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[455]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[456]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[457]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[458]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[459]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[460]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[461]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[462]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[463]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[464]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[465]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[466]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[467]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[468]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[469]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[470]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[471]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[472]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[473]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[474]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[475]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[476]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[477]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[478]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[479]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[480]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[481]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[482]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[483]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[484]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[485]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[486]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[487]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[488]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[489]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[490]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[491]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[492]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[493]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[494]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[495]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[496]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[497]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[498]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[499]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[500]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[501]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[502]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[503]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[504]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[505]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[506]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[507]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[508]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[509]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[510]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[511]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[512]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[513]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[514]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[515]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[516]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[517]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[518]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[519]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[520]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[521]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[522]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[523]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[524]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[525]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[526]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[527]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[528]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[529]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[530]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[531]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[532]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[533]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[534]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[535]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[536]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[537]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[538]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[539]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[540]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[541]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[542]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[543]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[544]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[545]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[546]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[547]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[548]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[549]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[550]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[551]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[552]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[553]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[554]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[555]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[556]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[557]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[558]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[559]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[560]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[561]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[562]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[563]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[564]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[565]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[566]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[567]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[568]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[569]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[570]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[571]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[572]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[573]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[574]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[575]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[576]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[577]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[578]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[579]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[580]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[581]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[582]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[583]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[584]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[585]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[586]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[587]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[588]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[589]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[590]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[591]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[592]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[593]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[594]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[595]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[596]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[597]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[598]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[599]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[600]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[601]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[602]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[603]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[604]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[605]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[606]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[607]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[608]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[609]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[610]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[611]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[612]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[613]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[614]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[615]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[616]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[617]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[618]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[619]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[620]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[621]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[622]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[623]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[624]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[625]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[626]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[627]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[628]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[629]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[630]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[631]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[632]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[633]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[634]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[635]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[636]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[637]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[638]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[639]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[640]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[641]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[642]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[643]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[644]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[645]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[646]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[647]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[648]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[649]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[650]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[651]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[652]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[653]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[654]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[655]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[656]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[657]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[658]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[659]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[660]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[661]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[662]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[663]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[664]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[665]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[666]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[667]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[668]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[669]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[670]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[671]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[672]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[673]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[674]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[675]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[676]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[677]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[678]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[679]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[680]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[681]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[682]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[683]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[684]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[685]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[686]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[687]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[688]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[689]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[690]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[691]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[692]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[693]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[694]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[695]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[696]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[697]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[698]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[699]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[700]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[701]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[702]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[703]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[704]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[705]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[706]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[707]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[708]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[709]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[710]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[711]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[712]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[713]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[714]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[715]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[716]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[717]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[718]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[719]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[720]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[721]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[722]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[723]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[724]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[725]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[726]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[727]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[728]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[729]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[730]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[731]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[732]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[733]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[734]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[735]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[736]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[737]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[738]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[739]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[740]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[741]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[742]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[743]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[744]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[745]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[746]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[747]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[748]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[749]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[750]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[751]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[752]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[753]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[754]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[755]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[756]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[757]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[758]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[759]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[760]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[761]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[762]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[763]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[764]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[765]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[766]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[767]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[768]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[769]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[770]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[771]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[772]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[773]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[774]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[775]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[776]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[777]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[778]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[779]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[780]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[781]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[782]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[783]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[784]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[785]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[786]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[787]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[788]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[789]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[790]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[791]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[792]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[793]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[794]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[795]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[796]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[797]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[798]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[799]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[800]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[801]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[802]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[803]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[804]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[805]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[806]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[807]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[808]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[809]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[810]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[811]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[812]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[813]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[814]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[815]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[816]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[817]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[818]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[819]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[820]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[821]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[822]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[823]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[824]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[825]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[826]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[827]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[828]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[829]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[830]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[831]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[832]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[833]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[834]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[835]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[836]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[837]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[838]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[839]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[840]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[841]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[842]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[843]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[844]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[845]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[846]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[847]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[848]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[849]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[850]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[851]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[852]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[853]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[854]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[855]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[856]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[857]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[858]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[859]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[860]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[861]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[862]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[863]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[864]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[865]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[866]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[867]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[868]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[869]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[870]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[871]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[872]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[873]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[874]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[875]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[876]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[877]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[878]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[879]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[880]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[881]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[882]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[883]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[884]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[885]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[886]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[887]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[888]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[889]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[890]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[891]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[892]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[893]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[894]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[895]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[896]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[897]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[898]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[899]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[900]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[901]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[902]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[903]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[904]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[905]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[906]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[907]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[908]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[909]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[910]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[911]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[912]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[913]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[914]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[915]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[916]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[917]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[918]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[919]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[920]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[921]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[922]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[923]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[924]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[925]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[926]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[927]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[928]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[929]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[930]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[931]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[932]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[933]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[934]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[935]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[936]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[937]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[938]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[939]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[940]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[941]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[942]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[943]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[944]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[945]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[946]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[947]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[948]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[949]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[950]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[951]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[952]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[953]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[954]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[955]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[956]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[957]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[958]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[959]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[960]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[961]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[962]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[963]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[964]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[965]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[966]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[967]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[968]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[969]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[970]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[971]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[972]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[973]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[974]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[975]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[976]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[977]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[978]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[979]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[980]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[981]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[982]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[983]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[984]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[985]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[986]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[987]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[988]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[989]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[990]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[991]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[992]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[993]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[994]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[995]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[996]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[997]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[998]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[999]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1000]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1001]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1002]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1003]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1004]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1005]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1006]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1007]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1008]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1009]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1010]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1011]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1012]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1013]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1014]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1015]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1016]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1017]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1018]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1019]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1020]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1021]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1022]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1023]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1024]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1025]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1026]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1027]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1028]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1029]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1030]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1031]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1032]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1033]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1034]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1035]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1036]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1037]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1038]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1039]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1040]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1041]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1042]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1043]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1044]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1045]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1046]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1047]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1048]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1049]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1050]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1051]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1052]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1053]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1054]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1055]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1056]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1057]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1058]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1059]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1060]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1061]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1062]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1063]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1064]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1065]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1066]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1067]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1068]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1069]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1070]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1071]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1072]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1073]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1074]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1075]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1076]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1077]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1078]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1079]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1080]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1081]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1082]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1083]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1084]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1085]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1086]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1087]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1088]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1089]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1090]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1091]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1092]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1093]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1094]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1095]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1096]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1097]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1098]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1099]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1100]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1101]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1102]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1103]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1104]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1105]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1106]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1107]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1108]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1109]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1110]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1111]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1112]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1113]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1114]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1115]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1116]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1117]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1118]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1119]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1120]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1121]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1122]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1123]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1124]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1125]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1126]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1127]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1128]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1129]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1130]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1131]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1132]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1133]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1134]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1135]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1136]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1137]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1138]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1139]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1140]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1141]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1142]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1143]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1144]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1145]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1146]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1147]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1148]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1149]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1150]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1151]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1152]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1153]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1154]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1155]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1156]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1157]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1158]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1159]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1160]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1161]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1162]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1163]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1164]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1165]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1166]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1167]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1168]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1169]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1170]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1171]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1172]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1173]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1174]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1175]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1176]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1177]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1178]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1179]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1180]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1181]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1182]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1183]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1184]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1185]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1186]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1187]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1188]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1189]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1190]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1191]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1192]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1193]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1194]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1195]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1196]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1197]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1198]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1199]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1200]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1201]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1202]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1203]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1204]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1205]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1206]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1207]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1208]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1209]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1210]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1211]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1212]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1213]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1214]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1215]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1216]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1217]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1218]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1219]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1220]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1221]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1222]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1223]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1224]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1225]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1226]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1227]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1228]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1229]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1230]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1231]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1232]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1233]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1234]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1235]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1236]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1237]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1238]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1239]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1240]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1241]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1242]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1243]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1244]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1245]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1246]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1247]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1248]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1249]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1250]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1251]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1252]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1253]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1254]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1255]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1256]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1257]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1258]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1259]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1260]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1261]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1262]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1263]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1264]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1265]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1266]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1267]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1268]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1269]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1270]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1271]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1272]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1273]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1274]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1275]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1276]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1277]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1278]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1279]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1280]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1281]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1282]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1283]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1284]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1285]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1286]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1287]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1288]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1289]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1290]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1291]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1292]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1293]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1294]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1295]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1296]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1297]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1298]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1299]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1300]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1301]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1302]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1303]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1304]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1305]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1306]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1307]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1308]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1309]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1310]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1311]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1312]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1313]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1314]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1315]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1316]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1317]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1318]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1319]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1320]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1321]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1322]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1323]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1324]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1325]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1326]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1327]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1328]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1329]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1330]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1331]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1332]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1333]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1334]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1335]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1336]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1337]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1338]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1339]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1340]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1341]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1342]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1343]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1344]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1345]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1346]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1347]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1348]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1349]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1350]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1351]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1352]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1353]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1354]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1355]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1356]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1357]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1358]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1359]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1360]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1361]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1362]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1363]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1364]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1365]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1366]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1367]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1368]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1369]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1370]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1371]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1372]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1373]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1374]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1375]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1376]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1377]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1378]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1379]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1380]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1381]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1382]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1383]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1384]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1385]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1386]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1387]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1388]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1389]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1390]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1391]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1392]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1393]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1394]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1395]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1396]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1397]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1398]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1399]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1400]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1401]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1402]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1403]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1404]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1405]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1406]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1407]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1408]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1409]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1410]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1411]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1412]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1413]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1414]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1415]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1416]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1417]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1418]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1419]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1420]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1421]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1422]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1423]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1424]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1425]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1426]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1427]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1428]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1429]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1430]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1431]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1432]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1433]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1434]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1435]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1436]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1437]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1438]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1439]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1440]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1441]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1442]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1443]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1444]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1445]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1446]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1447]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1448]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1449]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1450]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1451]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1452]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1453]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1454]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1455]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1456]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1457]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1458]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1459]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1460]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1461]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1462]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1463]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1464]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1465]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1466]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1467]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1468]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1469]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1470]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1471]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1472]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1473]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1474]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1475]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1476]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1477]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1478]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1479]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1480]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1481]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1482]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1483]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1484]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1485]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1486]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1487]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1488]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1489]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1490]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1491]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1492]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1493]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1494]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1495]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1496]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1497]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1498]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1499]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1500]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1501]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1502]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1503]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1504]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1505]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1506]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1507]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1508]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1509]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1510]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1511]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1512]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1513]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1514]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1515]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1516]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1517]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1518]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1519]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1520]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1521]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1522]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1523]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1524]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1525]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1526]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1527]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1528]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1529]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1530]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1531]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1532]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1533]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1534]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1535]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1536]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1537]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1538]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1539]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1540]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1541]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1542]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1543]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1544]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1545]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1546]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1547]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1548]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1549]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1550]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1551]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1552]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1553]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1554]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1555]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1556]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1557]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1558]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1559]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1560]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1561]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1562]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1563]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1564]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1565]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1566]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1567]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1568]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1569]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1570]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1571]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1572]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1573]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1574]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1575]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1576]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1577]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1578]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1579]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1580]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1581]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1582]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1583]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1584]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1585]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1586]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1587]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1588]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1589]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1590]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1591]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1592]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1593]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1594]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1595]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1596]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1597]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1598]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1599]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1600]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1601]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1602]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1603]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1604]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1605]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1606]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1607]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1608]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1609]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1610]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1611]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1612]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1613]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1614]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1615]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1616]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1617]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1618]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1619]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
#> 
#> [[1620]]
#> # A tibble: 1,620 × 13
#>    lda_model booster   eta max_depth gamma subsample colsample_bylevel nrounds
#>    <chr>     <chr>   <dbl>     <dbl> <dbl>     <dbl>             <dbl>   <dbl>
#>  1 k_5       gbtree   0.01         3     0      0.5               0.5        5
#>  2 k_5       gbtree   0.01         3     0      0.5               0.5       30
#>  3 k_5       gbtree   0.01         3     0      0.5               0.5       55
#>  4 k_5       gbtree   0.01         3     0      0.5               0.75       5
#>  5 k_5       gbtree   0.01         3     0      0.5               0.75      30
#>  6 k_5       gbtree   0.01         3     0      0.5               0.75      55
#>  7 k_5       gbtree   0.01         3     0      0.5               1          5
#>  8 k_5       gbtree   0.01         3     0      0.5               1         30
#>  9 k_5       gbtree   0.01         3     0      0.5               1         55
#> 10 k_5       gbtree   0.01         3     0      0.75              0.5        5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> #   xgb_model <list>, error <dbl>, importance <dt[,1]>
results |>
  arrange(error) |>
  slice_head(n=10) |>
  select(lda_model, xgb_model) |>
  map2("lda_model", "xgb_model", function(x, y) {
    class(x)
  })
#> $lda_model
#> NULL
#> 
#> $xgb_model
#> NULL
  # map2(["xgb_model"], xgb_data, function(k, dat) {
  #   xgb.importance(feature_names = colnames(dat), 
  #                  model = k)
  # })
  # pmap(function(df) {
  #   xgb.importance(feature_names = colnames(xgb_data[[df["lda_model"]]]), 
  #                  model = df["xgb_model"])
  # })
bst <- results |> arrange(error) |> slice_head(n = 1) |> pull(xgb_model)
xgb.importance(feature_names = colnames(xgb_data$k_5),
               model = bst[[1]])
#>    Feature        Gain      Cover  Frequency
#>     <char>       <num>      <num>      <num>
#> 1:       3 0.710412125 0.51914160 0.35483871
#> 2:       2 0.138388761 0.15035984 0.22580645
#> 3:       1 0.109168843 0.26949902 0.32258065
#> 4:       5 0.037005205 0.04255739 0.06451613
#> 5:       4 0.005025067 0.01844215 0.03225806
# importance <-  lapply(seq_along(xgb_models), function(i) {
#   xgb.importance(
#     feature_names = colnames(xgb_data[[i]]), 
#     model = xgb_models[[i]]
#   )
# }
# )
# names(importance) <- paste0("k_", k_values)
# importance
# xgb_preds <- lapply(seq_along(xgb_models), function(i) {
#   xgb_preds <- predict(xgb_models[[i]], xgb_data[[i]]$Test, reshape = TRUE)
#   xgb_preds <- as.data.frame(xgb_preds)
#   
#   colnames(xgb_preds) <- levels(y$luokka)
#   rownames(xgb_preds) <- y$kunta[!y$kunta %in% trainNames]
#   xgb_preds$PredictedClass <- factor(colnames(xgb_preds)[max.col(xgb_preds, ties.method='first')], levels = levels(y$luokka))
#   xgb_preds$ActualClass <- factor(y[!y$kunta %in% trainNames, ]$luokka, levels = levels(y$luokka))
#   xgb_preds
# })
# names(xgb_preds) <- paste0("k_", k_values)
# xgb_preds
# conf_matrix <- lapply(seq_along(xgb_data), function(i) {
#   confusionMatrix(xgb_preds[[i]]$ActualClass, xgb_preds[[i]]$PredictedClass)
# })
# names(conf_matrix) <- paste0("k_", k_values)
# conf_matrix